Analisis Pengaruh Variabel Penduga Cuaca Ekstrem di Kota Bengkulu dengan Menggunakan Statistical Product and Service Solutions (SPSS) - Simbolon, Mikael (Newton-Maxwell Journal of Physics, 2023)
The Bengkulu City area often experiences extreme weather with the potential for flooding and affects various types of human activities. This study aims to determine the effect of extreme weather predictor variables in Bengkulu City by using Statistical Product and Service Solutions (SPSS). Extreme weather indicators are  reviewed  based  on  rainfall  with  estimating  variables  in  the  form  of  air pressure, humidity, air temperature, and wind speed, for 5 years (2017-2021) obtained from the BMKG Station on Baai Island, Bengkulu City. Data processing using SPSS method. Data analysis was carried out statistically and descriptively. Based on the results of the study, the correlation between the estimator variables on extreme rainfall is quite good with r = 0.661, and the error value (RMSE) is 27,124. Furthermore, the homogeneity test between extreme rainfall indicators and extreme weather estimators   includes   air   pressure, air   temperature, wind   speed,  and   air   humidity,   showing homogeneity in 2019. This indicates the predictor variable has the same direction to extreme rainfall, where the error value is obtained tends to be relatively small. The estimator variables, namely air pressure and humidity, have a significant relationship with extreme rainfall. Predictions using data (2017-2021) show that in 2022, extreme rainfall events will occur for a relatively long time, namely in January, March, May, June, July, August, October, and December. The most extreme rainfall intensity occurs in January